code: def forward(self, x):
      x = self.conv1(x)
      x = self.pool1(x)
  
      x = self.block1(x)
      x = self.group1(x)
      x = self.pool2(x)
  
      x = self.block2(x)
      x = self.group2(x)
      x = self.pool3(x)
  
      x = self.block3(x)
      x = self.group3(x)
      x = self.block4(x)
      x = self.group4(x)
      x = self.pool4(x)
  
      x = x.view(x.size(0), -1)
      fc = self.fc(x)
  
      if self.training:
          x = F.dropout(fc, training=self.training)
          out = self.cosine_sim(x, self.weight)
          return out, F.normalize(fc, p=2, dim=1)
      return F.normalize(fc, p=2, dim=1)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import Parameter
label_desc: Use image node_id 4 for calling the network_29layers_cosface obj's underlying member method code with example usage: obj.forward(x) and returns: F, out,  F